MSBVH: An Efficient Acceleration Data Structure for Ray Traced Motion Blur
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1 MSBVH: An Efficient Acceleration Data Structure for Ray Traced Motion Blur Leonhard Grünschloß Martin Stich Sehera Nawaz Alexander Keller August 6, 2011
2 Principles of Accelerated Ray Tracing Hierarchical culling object list partitioning BVH
3 Principles of Accelerated Ray Tracing Hierarchical culling object list partitioning BVH
4 Principles of Accelerated Ray Tracing Hierarchical culling object list partitioning BVH
5 Principles of Accelerated Ray Tracing Hierarchical culling object list partitioning BVH
6 Principles of Accelerated Ray Tracing Hierarchical culling object list partitioning BVH
7 Principles of Accelerated Ray Tracing Hierarchical culling object list partitioning BVH
8 Principles of Accelerated Ray Tracing Hierarchical culling object list partitioning BVH
9 Principles of Accelerated Ray Tracing Hierarchical culling object list partitioning BVH
10 Principles of Accelerated Ray Tracing Hierarchical culling object list partitioning BVH
11 Principles of Accelerated Ray Tracing Hierarchical culling object list partitioning BVH bounded memory, but overlapping bounding volumes
12 Principles of Accelerated Ray Tracing Hierarchical culling object list partitioning BVH bounded memory, but overlapping bounding volumes spatial partitioning kd-tree
13 Principles of Accelerated Ray Tracing Hierarchical culling object list partitioning BVH bounded memory, but overlapping bounding volumes spatial partitioning kd-tree
14 Principles of Accelerated Ray Tracing Hierarchical culling object list partitioning BVH bounded memory, but overlapping bounding volumes spatial partitioning kd-tree
15 Principles of Accelerated Ray Tracing Hierarchical culling object list partitioning BVH bounded memory, but overlapping bounding volumes spatial partitioning kd-tree
16 Principles of Accelerated Ray Tracing Hierarchical culling object list partitioning BVH bounded memory, but overlapping bounding volumes spatial partitioning kd-tree
17 Principles of Accelerated Ray Tracing Hierarchical culling object list partitioning BVH bounded memory, but overlapping bounding volumes spatial partitioning kd-tree
18 Principles of Accelerated Ray Tracing Hierarchical culling object list partitioning BVH bounded memory, but overlapping bounding volumes spatial partitioning kd-tree
19 Principles of Accelerated Ray Tracing Hierarchical culling object list partitioning BVH bounded memory, but overlapping bounding volumes spatial partitioning kd-tree
20 Principles of Accelerated Ray Tracing Hierarchical culling object list partitioning BVH bounded memory, but overlapping bounding volumes spatial partitioning kd-tree
21 Principles of Accelerated Ray Tracing Hierarchical culling object list partitioning BVH bounded memory, but overlapping bounding volumes spatial partitioning kd-tree
22 Principles of Accelerated Ray Tracing Hierarchical culling object list partitioning BVH bounded memory, but overlapping bounding volumes spatial partitioning kd-tree
23 Principles of Accelerated Ray Tracing Hierarchical culling object list partitioning BVH bounded memory, but overlapping bounding volumes spatial partitioning kd-tree
24 Principles of Accelerated Ray Tracing Hierarchical culling object list partitioning BVH bounded memory, but overlapping bounding volumes spatial partitioning kd-tree nodes do not overlap, but reference duplication
25 SBVH Best of both worlds object list partitioning whenever overlap is small spatial partitioning otherwise
26 SBVH Best of both worlds object list partitioning whenever overlap is small spatial partitioning otherwise use spatial splits to build BVH with reference duplication
27 SBVH Best of both worlds object list partitioning whenever overlap is small spatial partitioning otherwise use spatial splits to build BVH with reference duplication
28 SBVH Best of both worlds object list partitioning whenever overlap is small spatial partitioning otherwise use spatial splits to build BVH with reference duplication
29 SBVH Best of both worlds object list partitioning whenever overlap is small spatial partitioning otherwise use spatial splits to build BVH with reference duplication
30 SBVH Best of both worlds object list partitioning whenever overlap is small spatial partitioning otherwise use spatial splits to build BVH with reference duplication
31 SBVH Best of both worlds object list partitioning whenever overlap is small spatial partitioning otherwise use spatial splits to build BVH with reference duplication
32 SBVH Best of both worlds object list partitioning whenever overlap is small spatial partitioning otherwise use spatial splits to build BVH with reference duplication
33 SBVH Best of both worlds object list partitioning whenever overlap is small spatial partitioning otherwise use spatial splits to build BVH with reference duplication
34 SBVH Best of both worlds object list partitioning whenever overlap is small spatial partitioning otherwise use spatial splits to build BVH with reference duplication How to support motion blur?
35 Multiple BVHs Sharing Identical Topology Convex combination of bounding boxes yields conservative BVH
36 Multiple BVHs Sharing Identical Topology Convex combination of bounding boxes yields conservative BVH
37 Multiple BVHs Sharing Identical Topology Example: linear interpolation at leaf level
38 Multiple BVHs Sharing Identical Topology Example: linear interpolation at leaf level
39 Multiple BVHs Sharing Identical Topology Example: linear interpolation at leaf level t=0 t=1
40 Multiple BVHs Sharing Identical Topology Example: linear interpolation at leaf level t=0 t=1
41 Multiple BVHs Sharing Identical Topology Example: linear interpolation at leaf level t=0 t=1
42 Multiple BVHs Sharing Identical Topology t=0 Example: linear interpolation at leaf level t=1 t=0.5
43 Multiple BVHs Sharing Identical Topology t=0 Example: linear interpolation at leaf level t=1 t=0.5 acceptable memory overhead
44 Multiple BVHs Sharing Identical Topology t=0 Example: linear interpolation at leaf level t=1 t=0.5 acceptable memory overhead allows for very tight bounding boxes for every ray time t
45 Interpolation and Spatial Splits Can a kd-tree be interpolated?
46 Interpolation and Spatial Splits Can a kd-tree be interpolated? objects can move across split planes thus node references change!
47 Interpolation and Spatial Splits Can a kd-tree be interpolated? objects can move across split planes thus node references change! hierarchy over convex hulls is inefficient
48 Interpolation and Spatial Splits Can a kd-tree be interpolated? objects can move across split planes thus node references change! hierarchy over convex hulls is inefficient splitting along time-axis requires lots of memory
49 Our Contribution Extend the SBVH to handle motion blur (MSBVH) by computing multiple bounding volumes per node using classic bounding volume interpolation traversal
50 Our Contribution Extend the SBVH to handle motion blur (MSBVH) by computing multiple bounding volumes per node using classic bounding volume interpolation traversal which includes spatial splits
51 Our Contribution Extend the SBVH to handle motion blur (MSBVH) by computing multiple bounding volumes per node using classic bounding volume interpolation traversal which includes spatial splits memory-efficient (MSBVH) reduced bounding volume overlap (MSBVH) Note: we assume the hierarchy is rebuilt per frame
52 Algorithm t=0 t=1
53 Algorithm t=0 t=0.5 t=1 1. Build the SBVH for t = 0.5 to determine topology
54 Algorithm t=0 t=0.5 t=1 1. Build the SBVH for t = 0.5 to determine topology 2. Compute partial primitives in leaf nodes
55 Algorithm t=0 t=0.5 t=1 1. Build the SBVH for t = 0.5 to determine topology 2. Compute partial primitives in leaf nodes
56 Algorithm t=0 t=0.5 t=1 1. Build the SBVH for t = 0.5 to determine topology 2. Compute partial primitives in leaf nodes 3. Compute corresponding bounds for t = 0 and t = 1
57 Algorithm t=0 t=0.5 t=1 1. Build the SBVH for t = 0.5 to determine topology 2. Compute partial primitives in leaf nodes 3. Compute corresponding bounds for t = 0 and t = 1
58 Algorithm t=0 t=1 1. Build the SBVH for t = 0.5 to determine topology 2. Compute partial primitives in leaf nodes 3. Compute corresponding bounds for t = 0 and t = 1 4. Propagate bounds to the parent nodes
59 Algorithm t=0 t=1 1. Build the SBVH for t = 0.5 to determine topology 2. Compute partial primitives in leaf nodes 3. Compute corresponding bounds for t = 0 and t = 1 4. Propagate bounds to the parent nodes 5. Interpolate these bounds during traversal
60 Triangles and AABB-Hierarchies under Linear Motion t=0 t=0.5 t=1 1. Use Sutherland-Hodgman to clip against leaf AABB 2. Results in barycentric coordinates of polygon vertices
61 Triangles and AABB-Hierarchies under Linear Motion t=0 t=0.5 t=1 1. Use Sutherland-Hodgman to clip against leaf AABB 2. Results in barycentric coordinates of polygon vertices 3. Compute transformed polygon for t = 0 and t = 1
62 Triangles and AABB-Hierarchies under Linear Motion t=0 t=0.5 t=1 1. Use Sutherland-Hodgman to clip against leaf AABB 2. Results in barycentric coordinates of polygon vertices 3. Compute transformed polygon for t = 0 and t = 1 4. Bound the transformed polygon
63 Triangles and AABB-Hierarchies under Linear Motion t=0 t=0.5 t=1 1. Use Sutherland-Hodgman to clip against leaf AABB 2. Results in barycentric coordinates of polygon vertices 3. Compute transformed polygon for t = 0 and t = 1 4. Bound the transformed polygon 5. No extra storage necessary
64 Clipping Displaced Subdivision Surfaces
65 Clipping Displaced Subdivision Surfaces 1. Subdivide along surface parametrization 2. Bound individual elements, e.g. using interval arithmetic
66 Clipping Displaced Subdivision Surfaces 1. Subdivide along surface parametrization 2. Bound individual elements, e.g. using interval arithmetic 3. Clip resulting bounding boxes 4. The union conservatively bounds the clipped primitive
67 Extensions two-level hierarchy: animated instances
68 Extensions two-level hierarchy: animated instances interpolate transformation matrix elements to force linear motion A(t)
69 Extensions two-level hierarchy: animated instances interpolate transformation matrix elements to force linear motion A(1/3) A(2/3) A(0) A(1)
70 Extensions two-level hierarchy: animated instances interpolate transformation matrix elements to force linear motion multiple motion segments
71 Extensions two-level hierarchy: animated instances interpolate transformation matrix elements to force linear motion multiple motion segments restricted to powers of two for propagation up the hierarchy
72 Extensions two-level hierarchy: animated instances interpolate transformation matrix elements to force linear motion multiple motion segments restricted to powers of two for propagation up the hierarchy
73 Extensions two-level hierarchy: animated instances interpolate transformation matrix elements to force linear motion multiple motion segments restricted to powers of two for propagation up the hierarchy higher-order interpolation
74 Extensions two-level hierarchy: animated instances interpolate transformation matrix elements to force linear motion multiple motion segments restricted to powers of two for propagation up the hierarchy higher-order interpolation refitting over multiple frames
75 Results BVH traversal with linear interpolation I reduced SAH cost I significantly less intersection tests Video
76 Results BVH traversal with linear interpolation I reduced SAH cost I significantly less intersection tests I often less traversal steps I about 20% rendering speed-up for many scenes
77 Summary In practice, works well for single frames helps well whenever SBVH helps increased build times (between BVH and kd-tree) prototype implemention in OptiX
78 Summary In practice, works well for single frames helps well whenever SBVH helps increased build times (between BVH and kd-tree) prototype implemention in OptiX spatial splits only avoid overlap for t = 0.5 topology determined for t = 0.5 problematic for incoherent motion
79 Weta Digital is hiring!
MSBVH: An Efficient Acceleration Data Structure for Ray Traced Motion Blur
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